Working on the Practical Machine Learning course final project, I found it interesting that, while intuitively it seemed to me that classification relied heavily on the identity of the user - feature 'user_name' was not even on the 20 most important variables for modeling the Random Forest predictor. It then occurred to me that identity might be indirectly derived from other features.

Following is a plot of 3 out of the 4 leading important variables, which shows how singling out a user might be done.